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Abstract:

A method for predicting wind conditions in a wind farm is provided. The
method includes the steps of: (a) measuring wind conditions including a
wind speed and a wind direction by means of wind condition measurement
devices disposed outside the wind farm; (b) compensating for an error
occurring while the wind conditions measured by the wind condition
measurement devices are reaching the wind farm; and (c) calculating wind
conditions in each wind turbine in the wind farm after a predetermined
time based on the wind conditions whose error is compensated in step (b).
According to the present invention, it is possible to stably operate the
wind farm and effectively operate the entire power grid associated with
the wind farm by accurately predicting the wind conditions after a
predetermined time to minimize the fluctuation in power output of the
wind farm due to a change in the wind conditions.

Claims:

1. A method for predicting wind conditions in a wind farm, the method
comprising the steps of: (a) measuring wind conditions including a wind
speed and a wind direction by means of wind condition measurement devices
disposed outside the wind farm; (b) compensating for an error occurring
while the wind conditions measured by the wind condition measurement
devices are reaching the wind farm; and (c) calculating wind conditions
in each wind turbine in the wind farm after a predetermined time based on
the wind conditions whose error is compensated in step (b), wherein step
(b) comprises the steps of: (b-1) compensating for the error based on
topographic conditions between the wind condition measurement devices and
the wind farm; and (b-2) compensating for the error based on conditions
of a form in which the wind turbines are disposed in the wind farm.

3. The method of claim 1, wherein step (b) further comprises, after step
(b-1), the step of (b-3) compensating for the error based on a turbulence
model obtained by modeling the formation of turbulence due to the
movement of wind.

4. The method of claim 1, wherein step (b) further comprises, after step
(b-1), the step of (b-4) compensating for the error based on atmospheric
conditions between the wind condition measurement devices and the wind
farm.

5. The method of claim 3, wherein step (b) further comprises, after step
(b-1), the step of (b-4) compensating for the error based on atmospheric
conditions between the wind condition measurement devices and the wind
farm.

Description:

CROSS-REFERENCE TO RELATED PATENT APPLICATION

[0001] This application claims the benefit of Korean Patent Application
No. 10-2012-0022817, filed on Mar. 6, 2012, in the Korean Intellectual
Property Office, the disclosure of which is incorporated herein in its
entirety by reference.

BACKGROUND OF THE INVENTION

[0002] 1. Field of the Invention

[0003] The present invention relates to a method for predicting wind
conditions in a wind farm and, more particularly, to a method used to
effectively operate a wind farm by accurately predicting wind conditions
arriving at each wind turbine in the wind farm after a predetermined time
based on the fact that the wind conditions measured by wind condition
measurement devices installed outside the wind farm vary depending on a
variety of variables on their way to the wind farm.

[0004] 2. Description of the Related Art

[0005] A wind turbine is a device that converts kinetic energy of wind
into electrical energy, and a wind farm is a place where several wind
turbines are installed and rotated by natural wind to obtain energy on
land or at sea.

[0006] The wind farm generates electricity using wind and thus is much
affected by wind conditions. Since the electrical energy generated by the
wind turbine is affected by the strength of fluctuating wind and thus
cannot maintain a constant level at all times, its quality is inferior to
those of conventional power generators. In order to produce electrical
energy of high quality, a power generator in a power grid should reserve
sufficient power so as to compensate for the increase and decrease in
power output of the wind turbine. However, since the power output of the
wind farm is highly variable depending on the change in wind conditions,
a large amount of power should be reserved to stably operate the power
grid, which as a result increases the cost of power generation. Since
this problem becomes severe when a large number of wind turbines are
interconnected to the power grid, a grid-code is established and enforced
in many countries of the world, and the Korea's grid-code was also
announced in June, 2010.

[0007] In preparation for the case when the wind disappears suddenly or
blows much less, it is necessary to have sufficient reserve power such
that other generators in the power grid can use the reserve power. To
this end, it is necessary to turn on a fuel generator with high
generation costs in advance, which causes the ineffective operation of
the power grid. Accordingly, only when the power output of the wind farm
after a predetermined time can be accurately predicted, it is possible to
reduce the amount of the reserve by the other operating generation units,
and thus effectively operate the power grid.

[0008] As a prior art, Korean Patent No. 10-1093003 discloses a technique
for controlling a wind farm when the wind speed varies abruptly. This
technique ensures reliability of the entire power grid by controlling the
ramp rate of the wind farm based on a change in the wind speed. However,
this is based on the assumption that the wind conditions measured outside
the wind farm arrive at the wind farm as they are, and thus it is
necessary to consider a situation where the wind conditions vary.

SUMMARY OF THE INVENTION

[0009] The present invention has been made in an effort to solve the
above-described problems associated with the prior art, and an object of
the present invention is to accurately predict wind conditions of each
wind turbine in a wind farm after a predetermined time.

[0010] Another object of the present invention is to stably operate a wind
farm and further effectively operate the entire power grid by accurately
predicting wind conditions after a predetermined time to minimize the
fluctuation in power output of the wind farm due to a change in the wind
conditions.

[0011] Still another object of the present invention is to effectively
control and operate a wind farm by predicting the power output of the
wind farm, reducing the rate of fluctuation of the wind farm, and
improving the power factor based on predicted wind condition information.

[0012] To achieve the above-described objects, the present invention
provides a method for predicting wind conditions in a wind farm, the
method comprising the steps of: (a) measuring wind conditions including a
wind speed and a wind direction by means of wind condition measurement
devices disposed outside the wind farm; (b) compensating for an error
occurring while the wind conditions measured by the wind condition
measurement devices are reaching the wind farm; and (c) calculating wind
conditions in each wind turbine in the wind farm after a predetermined
time based on the wind conditions whose error is compensated in step (b),
wherein step (b) comprises the steps of: (b-1) compensating for the error
based on topographic conditions between the wind condition measurement
devices and the wind farm; and (b-2) compensating for the error based on
conditions of a form in which the wind turbines are disposed in the wind
farm.

[0013] Moreover, the method for predicting wind conditions in a wind farm
in accordance with an exemplary embodiment of the present invention
further comprises, after step (b-1), the step of (b-3) compensating for
the error based on a turbulence model obtained by modeling the formation
of turbulence due to the movement of wind.

[0014] Meanwhile, the method for predicting wind conditions in a wind farm
in accordance with another exemplary embodiment of the present invention
further comprises, after step (b-1), the step of (b-4) compensating for
the error based on atmospheric conditions between the wind condition
measurement devices and the wind farm, and the wind condition measurement
devices are disposed in multiple layers outside the wind farm.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and other features and advantages of the present
invention will become more apparent by describing in detail exemplary
embodiments thereof with reference to the attached drawings in which:

[0020] Although the wind turbines are simply placed in the form of a
square in the wind farm in FIG. 1, the wind turbines may be placed in
various forms depending on the topography in actual design of the wind
farm, and it is more effective to design the wind farm to have a form
that can maximize the power output of the wind farm.

[0021] The wind condition measurement devices are installed outside the
wind farm. The installation positions of the wind condition measurement
devices are determined based on a time required for the wind, of which
conditions are measured by the wind condition measurement devices, to
arrive at the wind farm and based on the level of errors that may occur
on its way to the wind farm. The arrival time increases as the distance
increases, and thus it is advantageous to control the power output by
controlling the wind farm. However, the increased distance has more
factors that cause errors in the wind conditions, which makes it
difficult to accurately predict the wind conditions in the wind farm. On
the contrary, when the wind condition measurement devices are placed
close to the wind farm, it is possible to relatively accurately predict
the wind conditions in the wind farm. However, the arrival time of the
wind decreases, and thus it is necessary to control the wind farm within
a short time. Accordingly, the wind condition measurement devices are
placed in optimized positions within a distance range that can minimize
the errors in the prediction of the wind conditions in the wind farm and,
at the same time, can ensure the time required to control the wind farm.

[0022]FIG. 2 is a flowchart of a method for predicting wind conditions in
a wind farm in accordance with an exemplary embodiment of the present
invention.

[0023] In order to effectively operate a wind farm, it is important to
accurately predict the direction and speed of wind blowing on wind
turbines placed in the wind farm. When a wind condition measurement
device is placed in the same position as the wind turbine, it is possible
to obtain the most accurate wind condition information. However, in this
case, it is only possible to measure in real time the wind conditions in
the wind farm, but it is not possible to predict the wind conditions
after a predetermined time, which makes it difficult to associate the
wind conditions with the operation of the entire power grid. Accordingly,
it is necessary to place the wind condition measurement devices at
predetermined distances from the wind farm and predict the wind condition
information in the wind farm after a predetermined time based on the
measurement results of the wind condition measurement devices.

[0024] The method for predicting wind conditions in a wind farm in
accordance with an exemplary embodiment of the present invention
comprises the steps of (a) measuring wind conditions including a wind
speed and a wind direction by means of wind condition measurement devices
disposed outside the wind farm, (b) compensating for an error occurring
while the wind conditions measured by the wind condition measurement
devices are reaching the wind farm, and (c) calculating wind conditions
in each wind turbine in the wind farm after a predetermined time based on
the wind conditions whose error is compensated in step (b).

[0025] Step (b) comprises the steps of (b-1) compensating for the error
based on topographic conditions between the wind condition measurement
devices and the wind farm, and (b-2) compensating for the error based on
conditions of a form in which the wind turbines are disposed in the wind
farm.

[0026] The wind, of which conditions are measured by the wind condition
measurement devices, may have errors caused by various factors while the
wind is reaching the wind farm. In the present invention, the factors are
generally classified into three factors to apply a method for
compensating for an error due to each factor.

[0027] The first step of compensating for an error in wind conditions is
based on topographic conditions between the wind condition measurement
devices and the wind farm. The topographic conditions that result in a
change in the wind conditions include properties, height, and form of the
ground surface, and the properties of the ground surface depend on
whether the ground surface is at sea or on land and, in the case of the
ground surface on land, depend on whether the ground surface is flat or
whether it is on snow, on grass, or in a copse. When the properties of
the ground surface vary, the friction between the wind and the ground
surface varies, and thus the properties of the ground surface affect the
wind conditions. Meanwhile, although the wind blows on the same ground
surface, the influence of the wind from the ground surface depends on the
height, and thus the degree of change in the wind conditions varies
depending on the height. The properties of the ground surface and the
influence of the height can be represented by the following formula 1:

V h = V l ( ln h z 0 ln l z 0 ) [ m
/ s ] [ Formula 1 ] ##EQU00001##

[0028] wherein h and l are the heights from the ground, Vh and
Vl are the wind speeds at the corresponding heights, and z0 is
the coefficient of roughness.

[0029] For reference, the coefficient of roughness z0 obtained from
cumulative data is shown in the following table 1:

[0030] The form of the ground surface depends on whether the ground
surface is bent or whether the ground surface is hilly or flat.

[0031] Meanwhile, the topographic conditions around the wind farm are not
easily changed. That is, the properties, form, etc. of the wind farm are
variables that rarely change. Accordingly, when an error due to a
variable is reflected, it is advantageous to derive statistical data by
accumulating the calculated topographic conditions and to perform a
statistical application, instead of a real-time calculation. The
properties of the ground surface differ slightly depending on the season,
the growth of plants, the snow cover, etc. However, the properties of the
ground surface have a repetitive pattern on a yearly basis, and thus it
is easy to perform the statistical application. Moreover, the form of the
ground surface around the wind farm hardly changes, and thus it is also
easy to perform the statistical application. Accordingly, the exemplary
embodiment of the present invention includes applying the statistical
data as well as the real-time calculation to reflect the topographic
conditions to the error in the wind conditions.

[0032] Meanwhile, the method for predicting wind conditions in a wind farm
of the present invention comprises, after step (b-1), the step of (b-2)
compensating for the error based on conditions of the form in which the
wind turbines are disposed in the wind farm.

[0033] In step (b-2), the error in the wind conditions are compensated
based on the influence exerted between the wind turbines in the wind farm
as well as based on the change in the wind conditions occurring between
the wind condition measurement devices and the wind farm. The influence
exerted between the wind turbines differs depending on the form in which
the wind turbines are disposed in the wind farm, and thus the influence
is reflected in the compensation.

[0034] In the case where a plurality of wind turbines are installed in
multiple layers in the wind farm as shown in FIG. 1, when a blade of the
wind turbine, located in a layer where the wind arrives first, is rotated
by the wind, the wind rotating the blade arrives at the next wind turbine
with a change in the wind conditions. That is, even when the same wind
blows on the wind farm, the speed and angle of the wind rotating each
wind turbine vary depending on the position where the wind turbine is
placed. Accordingly, it is possible to more accurately predict the wind
conditions reaching each wind turbine of the wind farm by calculating the
change of the wind operating the wind turbine based on the influence of a
slipstream created by the blade of the wind turbine on other wind
turbines.

[0035] The slipstream created by the rotation of the wind turbine
increases the intensity of turbulence, increases the fatigue load due to
a reduction in momentum of the wind turbines placed behind, and reduces
the entire power output of the wind farm due to a reduction in the speed
of the wind. Accordingly, the present invention predicts an inflow wind
speed in the wind turbine affected by the slipstream and thus predicts
the wind conditions in the wind turbine located in the position of the
slipstream.

[0036] To predict the wind direction in the wind turbine affected by the
slipstream, various standardized models may be used and, as an example,
when an eddy viscosity model by Ainslie is used it is written in the
following formula 2:

[0037] wherein the rotation of the wind turbine is applied to a
cylindrical coordinate system, r is the displacement in a radial
direction of the cross section of the rotating blade of the wind turbine,
x is the displacement in a direction that the wind flows in the wind
turbine, V is the wind speed in the r direction, U is the wind speed in
the x direction (the speed of wind causing power generation), and
ε is the coefficient indicating an eddy viscosity.

[0039] where k is the Von Kerman constant and I0 is the turbulence
intensity.

[0040] Accordingly, when the Ainslie model described in formula 2 and
formula 3 is used, it is possible to predict the inflow wind speed in the
wind turbine affected by the slipstream created by the rotation of the
wind turbine and thus to predict the wind conditions in the wind turbine
located in the position of the slipstream.

[0041] The method for predicting wind conditions in a wind farm in
accordance with an exemplary embodiment of the present invention further
comprises, after step (b-1), the step of (b-3) compensating for the error
based on a turbulence model obtained by modeling the formation of
turbulence due to the movement of wind.

[0042] In the present embodiment, the turbulence model is to compensate
for an error due to turbulence when applying the topographic conditions.

[0043] The wind has an irregular flow due to various factors, which is
referred to as turbulence, and the turbulence in the wind power
generation is a factor causing a reduction in power generation and an
increase in the system load. Accordingly, when the influence of the
turbulence is reflected, it is possible to predict the wind conditions in
the wind farm and thus to effectively control the wind farm, thereby
stably operating the entire power grid.

[0044] To reflect the influence of the turbulence, it is necessary to
calculate the turbulence intensity, an index indicative of the intensity
of the turbulence. The turbulence intensity I is calculated by the
following formula 4:

I = D 1 / 2 V m [ Formula 4 ] ##EQU00004##

[0045] wherein D1/2 is the standard deviation of the wind speed and
Vm is the average wind speed.

[0046] To obtain the turbulence intensity, information on the standard
deviation of the wind speed and the average wind speed is required and
may be obtained from the wind condition information whose error is
compensated by the topographic conditions.

[0047] Based on the information on the wind speed obtained by applying the
topographic conditions, the above formula 4 can be represented by the
following formula 5:

[0048] It is possible to determine the occurrence frequency of turbulences
by calculating the turbulence intensity based on formula 5, and it is
possible to predict the change in the wind conditions in the wind farm
after a predetermined time based on the occurrence frequency of
turbulences

[0049] Meanwhile, the method for predicting wind conditions in a wind farm
in accordance with another exemplary embodiment of the present invention
further comprises, after step (b-1), the step of (b-4) compensating for
the error based on atmospheric conditions between the wind condition
measurement devices and the wind farm.

[0050] The reflection of the atmospheric conditions between the wind
condition measurement devices and the wind farm includes reflecting a
change in wind conditions in the wind farm due to changes in temperature
and atmospheric pressure between the wind condition measurement devices
and the wind farm.

[0051] As an example of predicting the change in the wind conditions due
to the changes in the temperature and atmospheric pressure, it is
possible to calculate a change in air density due to the changes in the
temperature and atmospheric pressure and to reflect the influence of the
change in air density on the wind speed and wind direction.

[0052] The air density ρ with respect to the temperature and
atmospheric pressure can be calculated by the following formula 6:

[0053] wherein t is the temperature (° C.), P is the atmospheric
pressure, and e is the atmospheric vapor pressure.

[0054] Referring to formula 6, when the changes in the temperature and
atmospheric pressure between the wind condition measurement devices and
the wind farm are reflected, it is possible to accurately predict the air
density. That is, since the movement of the wind is interrupted at a
higher air density, the wind speed decreases in an area where the air
density is high between the wind condition measurement devices and the
wind farm, and the wind tends to blow toward an area where the air
density is low, which also affects the wind direction.

[0055] Accordingly, when the wind conditions are predicted based on the
atmospheric conditions, it is possible to more accurately predict the
wind conditions, compared to that based on the topographic conditions,
and it is advantageous to consider the influence of the changes in the
temperature and atmospheric pressure.

[0056] Meanwhile, the wind condition measurement devices of the present
invention may be disposed in multiple layers outside the wind farm. In
this case, it is possible to predict the wind conditions changed in the
wind farm by analyzing the change in the wind conditions measured by the
wind condition measurement devices disposed in several layers outside the
wind farm.

[0057] As such, the method for predicting wind conditions in a wind farm
of the present invention predicts the wind conditions in the wind farm
based on the factors that change the wind conditions between the wind
condition measurement devices and the wind farm. In particular, the
factors that affect the wind conditions are generally classified into
three factors. First, the topographic conditions, which are the most main
factor but have a low fluctuation over time, are mainly applied, and the
slipstream, which has a significant effect on the change in the wind
conditions, is applied to the compensation of the error among various
factors that change the wind conditions in the wind farm. Moreover, the
turbulence model reflecting the momentary change in the wind conditions
and the atmospheric conditions affected by the temperature and
atmospheric pressure are applied to increase the accuracy of the
prediction of the wind conditions in each wind turbine in the wind farm.

[0058] According to the present invention, it is possible to consider all
of the internal and external factors of the wind farm, and thus it is
possible to accurately predict the wind conditions in each wind turbine
in the wind farm after a predetermined time.

[0059] In particular, according to the present invention, it is possible
to accurately predict the speed and direction of the wind that blows in
the wind farm within several minutes to several hours, and thus it is
possible to predict and control the amount of wind power generation
within a very short time.

[0060] As described above, according to the present invention, it is
possible to accurately predict the wind conditions of each wind turbine
in the wind farm after a predetermined time.

[0061] Moreover, it is possible to stably operate the wind farm and
further effectively operate the entire power grid associated with the
wind farm by accurately predicting the wind conditions after a
predetermined time to minimize the fluctuation in power output of the
wind farm due to a change in the wind conditions.

[0062] Furthermore, it is possible to effectively control and operate the
wind farm by predicting the power output of the wind farm, reducing the
rate of fluctuation of the wind farm, and improving the power factor
based on predicted wind condition information.

[0063] While the invention has been shown and described with reference to
certain exemplary embodiments thereof, it will be understood by those
skilled in the art that various changes in form and details may be made
therein without departing from the spirit and scope of the invention as
defined by the appended claims. Therefore, the scope of the invention is
defined not by the detailed description of the invention but by the
appended claims, and all differences within the scope will be construed
as being included in the present invention.

Patent applications by Yeon Hee Kim, Wanju-Gun KR

Patent applications by Yong Cheol Kang, Jeonju-Si KR

Patent applications by INDUSTRIAL COOPERATION FOUNDATION CHONBUK NATIONAL UNIVERSITY